Creation and optimization of security applications for cyber threats detection, investigation and mitigation

ABSTRACT

A system and method for optimizing a defense model using available security capabilities are provided. The method includes obtaining a defense model and an optimal security application implementation associated with the defense model; evaluating available security capabilities deployed in an enterprise environment to determine a plurality of variant security applications implementing the defense model; determining a quality score for each of the plurality of the variant security applications; selecting, from the plurality of variant security applications, a variant security application having a highest quality score; and executing the selected variant security application.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Patent Application Ser. No.62/532,130 filed Jul. 13, 2017, which is hereby incorporated byreference for all that it contains.

TECHNICAL FIELD

The present disclosure relates generally to cyber security systems, andmore particularly to real-time creation and optimization of securityapplications utilized in such systems.

BACKGROUND

The frequency and complexity level of cyber-attacks has increased withrespect to attacks performed against cloud providers, enterprises,organizations, network carriers, and the like (collectively referred toas “enterprises” or “enterprise”). Some complex attacks, known asmulti-vector attack campaigns, utilize different types of attacktechniques and target network, servers and end point applications inorder to identify at least one weakness that can be exploited to achievethe attack's goals, thereby compromising the entire security frameworkof the network.

To secure their systems, infrastructure, and services, enterprisesutilize many different security products provided by different vendors.Typically, such products are utilized to detect and/or mitigatedifferent vulnerabilities or threats. As an example, an enterprisenetwork can implement one security product for an intrusion detectionsystem (IDS) and another product for detecting malware download.Particularly, a typical enterprise network will be protected by a set ofsecurity services that may include firewalls, anti-virus software,malware detection software, authentication and authorization systems,intrusion detection, anti-phishing systems, network and end pointbehavior analysis, data leak prevention systems, web applicationfirewalls (WAFs), and so on. The security products are typicallydeployed in different segments of the enterprise network, e.g., atdifferent servers, end-points (client computers), networks, and so on.Further, similar products from different vendors, can typically beutilized in combination to enhance security.

The complexity of security systems requires expertise in configuring andorchestrating the various components of a security system. Inparticular, to allow proper operation of such systems, a defense modelhas to be defined against a particular cyber threat. Specifically, adefense model defines, among other things, the system's components(security capabilities) to optimally detect investigate and mitigate thethreats. The model also defines the correlation rules between securityevents and the investigation and mitigation actions that should beexecuted. The detection, investigation, and mitigation would requiremonitoring, classifying, and correlating attack logs from multiplesecurity products.

However, still complex attacks are frequently successful because modernsecurity systems are not sufficiently orchestrated, in and agile andadaptive manner with respect to detection, investigation and mitigationof such evolving threats. Current security systems cannot easily andpromptly adapt to detect and mitigate new attack (threat) behavior, orattacks that change their behavior in a significant manner.

To improve responsiveness to cyber threats, an attempt is made to shareand collaborate on information regarding threats and vulnerabilities.Such a collaboration potentially may allow security subject matterexperts to analyze it and then to define prevention actions andconfigurations against some of the basic, and single vector attacks.However, currently there are no solutions that allow efficientcollaboration and timely execution of advanced defense models againstmulti-vector advanced attack campaigns and threats. One of the reasonfor this deficiency is the architecture of the security systems.

As noted above, a security system to protect an organization is a myriadof security products, with various security capabilities, by differentvendors. Each such product has a unique interface and implements adifferent type of technology, configurations, debug methods, differentsecurity rules, and logs. The myriad of different security solutionsand, specifically, their security rules pose a great challenge toprotecting an enterprise network from cyber-attacks. In addition to thecomplexity in configuring and mainly in monitoring the differentsolutions, there is a real challenge in understanding the effectivenessof each security rule and, consequently, each solution. That is, itcannot be easily determined which solution, for example, is better overthe other to detect a specific type of threat.

As such, currently there is no solution that can automatically adapt thedefense model to work optimally according to the existing securitycapabilities (e.g., products by various vendors) in each environment.Thus, each organization, based on the security threat information, needto determine and builds its own defense models and its own proceduresfor (automatically, or manually) orchestrate the tools deployed in hisorganization to effectivity detect and mitigate the cyber threats. Thisprocess often requires human expertise and time, thereby significantlyincreasing the time to detect and the time to respond to attacks.

Another deficiency with existing solutions is that such defense modelsand procedures are not agile to changes in the security capabilities.For example, a failure of a single security product may break thedefense model and prevent the detection and/or mitigation of a cyberthreat.

Furthermore, the current management, configuration, monitoring andorchestrating of various security products in the organization is acomplex task and typically requires months of programming work toaccomplish. As a result, current solutions for protect large scaleenterprise networks are not easily adaptable to protect against ongoingsecurity threats.

It would therefore be advantageous to provide a solution that wouldovercome the deficiencies of the prior art.

SUMMARY

A summary of several example embodiments of the disclosure follows. Thissummary is provided for the convenience of the reader to provide a basicunderstanding of such embodiments and does not wholly define the breadthof the disclosure. This summary is not an extensive overview of allcontemplated embodiments, and is intended to neither identify key orcritical elements of all embodiments nor to delineate the scope of anyor all aspects. Its sole purpose is to present some concepts of one ormore embodiments in a simplified form as a prelude to the more detaileddescription that is presented later. For convenience, the term “someembodiments” may be used herein to refer to a single embodiment ormultiple embodiments of the disclosure.

Some embodiments disclosed herein include a method for optimizing adefense model using available security capabilities. The systemcomprising obtaining a defense model and an optimal security applicationimplementation associated with the defense model; evaluating availablesecurity capabilities deployed in an enterprise environment to determinea plurality of variant security applications implementing the defensemodel; determining a quality score for each of the plurality of thevariant security applications; selecting, from the plurality of variantsecurity applications, a variant security application having a highestquality score; and executing the selected variant security application.

Some embodiments disclosed herein also include a system for optimizing adefense model using available security capabilities. The systemcomprising a processing circuitry; a memory coupled to the processingcircuitry, the memory contains therein instructions that when executedby the processing circuitry configure the system to: obtain a defensemodel and an optimal security application implementation associated withthe defense model; evaluate available security capabilities deployed inan enterprise environment to determine a plurality of variant securityapplications implementing the defense model; determine a quality scorefor each of the plurality of the variant security applications; select,from the plurality of variant security applications, a variant securityapplication having a highest quality score; and execute the selectedvariant security application.

BRIEF DESCRIPTION OF THE DRAWINGS

The subject matter disclosed herein is particularly pointed out anddistinctly claimed in the claims at the conclusion of the specification.The foregoing and other objects, features, and advantages of thedisclosed embodiments will be apparent from the following detaileddescription taken in conjunction with the accompanying drawings.

FIG. 1 is an example diagram illustrating the deployment of acyber-security system in an enterprise environment demonstrating theoperation of the disclosed embodiments.

FIG. 2 is a diagram of a security stack implemented by thecyber-security system according to an embodiment.

FIG. 3 is a schematic diagram illustrating a base security applicationand a variant of the base security application generated thereof.

FIG. 4 is a flowchart illustrating a method for creating and optimizinga security application according to one embodiment.

FIG. 5 is a diagram of a security service demonstrating the computationof the performance scores according to an embodiment.

FIG. 6 is a hardware block diagram of a security stack systemimplemented according to an embodiment.

DETAILED DESCRIPTION

It is important to note that the embodiments disclosed herein are onlyexamples of the many advantageous uses of the innovative teachingsherein. In general, statements made in the specification of the presentapplication do not necessarily limit any of the various claimedembodiments. Moreover, some statements may apply to some inventivefeatures but not to others. In general, unless otherwise indicated,singular elements may be in plural and vice versa with no loss ofgenerality. In the drawings, like numerals refer to like parts throughseveral views.

According to the disclosed embodiments, a method and system that allowsfor creating and optimizing security applications in real-time areprovided. A security application is an implementation of the defensemodel using a set of security products. A security application iscreated and/or optimized based on a defense model. The defense modeldefines the optimal defense behavior with respect to a certain threat.

In an embodiment, a deployed and operable security application ismonitored to determine if such an application is fully optimized toimplement the defense model based on the currently available set ofsecurity products in the organization. Therefore, according to thedisclosed embodiments, in a case of temporary failure, dysfunction ofone or more security products, or lack of required securityfunctionality in one or more of the existing security products, asecurity application can be dynamically adapted to fit a current set ofavailable products, ensuring that the enterprise is protected also whenthere are failures.

In another embodiment, the defense models and the security applicationsare agnostic to any type of a security product (device and/or service)deployed in the enterprise. As such, the defense models and securityapplications can be shared across different security applicationsdeployed in different enterprises.

FIG. 1 is an example diagram illustrating the deployment of acyber-security orchestration system 110 in an enterprise environment 100demonstrating the operation of the disclosed embodiments. The enterpriseenvironment 100 may include, for example, cloud providers, enterprises,organizations, business, network carriers, and the like.

The cyber-security orchestration system 110 (or the “system 110”) isconfigured to protect an entity (hereinafter a “protected entity”) 130communicatively connected in a network 120. The network 120 may be, butis not limited to, a virtualized network, a software defined network(SDN), a hybrid network, a cloud services network, or any combinationthereof. In an embodiment, the cyber-security system 110 is configuredto operate in detection, investigation, and mitigation phases.

In an example configuration, the cyber-security system 110 is configuredto control and execute the various phases to protect the protectedentity 130. Specifically, the cyber-security system 110 is configured tocreate, control, program, and execute a plurality of securityapplications (collectively labeled as “security app 211”).

The security applications 211 can be downloaded from a centralrepository 160, which may be connected to the system 110 through anetwork, such as but not limited to, the network 120. In an embodiment,the central repository 160 stored a plurality of security applicationsand defense models that can be shared among a plurality ofcyber-security systems. That is, a security application 211 executed bythe system 110 can be stored in the repository 160 and later utilized bya different cyber-security platform.

In an embodiment, the system 110 includes a classifier (not shown inFIG. 1) utilized to classify a plurality of attack protection rules andalerts of the various security products to the security services andsecurity engines realized through the system 110. The operation of thesystem 110 is discussed in greater detail herein below.

In an embodiment, the system 110 further includes a network interface113 configured to provide an interface layer for the system 110. Suchcommunication can be with SDN-based network elements or “legacy” networkelements (not shown) in the network 120. The network interface 113supports bi-directional communication drivers to allow communicationwith the data-plane elements including configurations, policy read, logscollection and API calls to query data repositories (logs DBs). Thedrivers support different forms of communication standards andvendor-defined interfaces such as Netconf, Netflow, BGP, BGP flow spec,SSH, CLIs, DB APIs and more. The drivers enable communication withmiddle-box devices (e.g., L4-L7 devices, DPI devices), end point devices(mobile, host-based security applications), server applications,management systems of these devices, other data repositories (e.g.,elastic search DB) and so on.

The network interface 113 also interfaces with a plurality of securityproducts 150 deployed in the enterprise environment 100. A securityproduct 150 collectively referred to a product, device, service and thelike that implement a security function to detect, investigate ormitigate a cyber threat. A security product 150 may maintain an attackdatabase (not shown in FIG. 1) including security rules. As noted above,the security rules typically include attack signatures, malware andvirus file patterns, malware OS related operation patterns and the liketo detect a threat, mitigate a threat, or both. An attack database isfrequently updated with new rules, modified rules, or both in order thatthe rules will be updated with the most recent threat intelligence aboutattack campaigns, new version of malware and viruses, and so on.

Following are non-limiting examples for cyber-solutions and associatedrules stored in their attack databases. The cyber-solution is ananti-virus system and the respective security rules may include virusfile patterns generated by anti-virus products, such as those providedby McAfee®, Symantec®, Blue Coat®, and the like. The cyber-solution isan Integrated Project Services (IPS) or intrusion detection system (IDS)and the respective rules are network attack signatures generated byproducts such as those provided by Source Fire® (Cisco), McAfee®,Snort®, and the like. The cyber-solution is an anti-malware system andthe respective rules are known anti-malware file patterns and OS relatedmalware action-patterns as provided by tools such as, but not limitedto, FireEye®, Lastline®, and the like.

During runtime, a security product 150 generates attack logs identifyingactivity (malicious or non-malicious) detected in the network 120. Anattack log is typically in a structured format that may vary fromproduct to product. For example, a single log (e.g., file) may containidentified hosts, users, network address and the type of activity (e.g.,event) detect by the security product 150. The attack logs are generatedand input to the system 110 at runtime, i.e., when a security product150 is active in detecting, investigating, or mitigating an on-goingattack, or a combination thereof.

The system 110 is configured to orchestrate the operation of the varioussecurity products 150 through execution of a plurality of securityapplications 211. According to the disclosed embodiments, the system 110is configured to create the applications 211 and modified theapplications 211 in real time to provide an optimal protection againstthreats at any given time. The optimal protection is achieved bycreating a security application utilizing available products 150 havingthe highest score in defensing against a particular threat.

For example, if two or more security products 150 are deployed toprotect the entity 130 against the same threat (e.g., spyware orransomware malware), either only one product having the highestperformance score will be selected for activating the protection forthat purpose at a time or only logs associated with this threat from oneproduct will be taken into account. In another embodiment, theorchestration system 110 may collect all logs, and prioritize such logsbased on the performance score associated with the product thatgenerated a respective log. The selection is based on a performancescore, or scores generated or otherwise computed for each securityproduct 150 and predefined selection criteria. In an embodiment, theweighting or prioritization of such logs is also based on is based on aperformance score.

The performance score includes any of an offline score, a runtime score,a unified score, or a combination thereof. An offline score is based onthe security-rules defined in an attack database (not shown) of arespective security product 150. As such attack database is typicallypopulated with rules, the score can be computed as an off-line processand not based on the runtime operation of the product 150. It should benoted that, as the security rules in an attack database are updated,added, or removed, a new off-line score can be generated or computed. Aruntime score is generated based on attack logs provided by a securityproduct 150. A unified score is at least based on the off-line andrun-time scores.

It should be noted that, for some security products 150, only a runtimescore can be generated or otherwise computed. As an example, for asecurity product 150 having an attack database containing security rulesthat frequently change, an off-line score will not be generated.

In an embodiment, the system 110 includes the classifier (not shown inFIG. 1) utilized to classify a plurality of attack protection rules andalerts of the various security products, and raw logs (e.g., Domaincontroller logs, DNS logs etc.) generated by the network infrastructure,to the security services and security engines realized through thesystem 110. The operation of the system 110 is discussed in greaterdetail herein below with respect to FIG. 2.

In an embodiment, the system 110 is configured to determine the intentof a detected cyber threat (new or existing) and create a defense modelthat can handle the threat. The defense model, when applied, can bedynamically adapted based on the available security product (devices andservices). In an embodiment, the intent of a cyber threat can bedetected based on a risk chain mechanism. An example for such amechanism is disclosed in U.S. patent application Ser. No. 15/239,258,assigned to the common assignee and it is hereby incorporated byreference for that it contains.

In an embodiment, the defense model and the security application areagnostic to any type of a security product (device and/or service)deployed in the enterprise. As such, the security application can act onany log, signal, and/or event received from such products.

In an embodiment, products defined in the defense model are selectedbased on a score determining how good a security product performs inprotecting against threat types. Thus, the defense model can be adaptedto select a specific product that would provide optimal defense againsta specific type of threat.

In an example embodiment, the defense model, and hence the securityapplication provides a unified abstract representation that is agnosticto the security products used for detection and mitigation of a threat.Thus, a security application created using the disclosed embodiment canbe utilized to protect the overall enterprise network without beingdependent on a specific security product (e.g., product). That is, onesecurity product can be replaced by another without changing orreconfiguring such a security application. Furthermore, the defensemodel, and hence the security application being agnostic to a specificsystem or infra-structure, can thus be easily collaborated and utilizedto protect other enterprises with little to no modifications.

According to the disclosed embodiments, the system 110 is configured tofirst receive or otherwise generate a defense model. In order togenerate a defense model, the system 110 is configured to determine anintent of a detected cyber threat (new or existing) and create a defensemodel that can handle the threat. The defense model provides a referenceto an optimal (base) security application that would provide the bestprotection against the protected entity 130. In one embodiment, thedefense model can be saved in the central repository 160.

Then, the system 110 is configured to determine the currently availablesecurity capabilities (in the environment 100) and their performancescores. As will be discussed below, the security capabilities includesecurity engines operable in the system 110. Each such engine isassociated with a security product 150. Thus, a performance score is ofa security product.

The system 110, is further configured to create at least one newsecurity application based on the defense model and the availablesecurity capabilities. The at least one new security application is avariant of the base security application (defined through the defensemodel). In an embodiment, a variant having the highest quality scoreamong all the at least one new application is deployed and executed.

Execution of a security application is performed by the system 110 byprocessing events and/or signals generated by the various products 150according to one or more correlation (workflow) rules, and/or accordingto a risk-chain model that identify cause-and-effect correlation betweenthe events, automatically. The processing of events and signals areperformed by security services and engines (discussed below) which areconfigured with the security application.

Continuously or periodically during the execution of a securityapplication, the changes in the security capabilities may be monitored.Any change that effects the executed application, as detected throughthe monitoring, can trigger a customization of the application so it canbe optimized to the current available capabilities. Therefore, in a caseof a temporary failure or dysfunction of one or more security products,an application 211 can be dynamically adapted to fit a current set ofavailable security capabilities, ensuring the continuous defense of theprotected entity 130. Any new applications or an optimized variantthereof can be saved in the central repository 160.

It should be emphasized that in addition to replacing a new (optimized)variant of a security application with an existing variant in the caseof a failure or dysfunction of a security capability, or lack ofsecurity capability, the replacement can be also made in other cases aswell. In particular, the replacement can be made if a better capabilityis now available. In another embodiment, a monetization factor can beutilized. The utilization of the monetization factor can be expressed aswhat are the best alternative set of available capabilities thatprovides the optimal protection as defined in the defense model.

In an embodiment, a variant of a base security application can beretrieved from the central repository 160, if such exists. Adetermination if such a variant exists is determined in part, based on,the available capabilities and the defense model.

FIG. 2 shows an example block diagram of a security stack 200implemented by the system 110 according to an embodiment. In an exampleconfiguration, the security stack 200 includes a security applicationsunit 210, a security services unit 220, a data-plane unit 230, anorthbound interface (NBI) 240, and a defense model optimizer (DMO) 270.The security stack 200 also includes security services 221 that arereusable across different security applications (“apps”) 211. Thus,different security applications 211 (each security application 211typically configured for a different purpose) can consume the samesecurity services 221 for their own needs.

Specifically, the security applications unit 210 includes one or moresecurity applications 211. Each security application 211 represents adifferent type of security protection including, for example, ransomwareattack campaign detection and mitigation, intelligence gatheringdetection and mitigation, insider threat detection and mitigation,data-leaks, and so on. The modules or rules interfacing with a securityapplication 211 provide the required services and security engines 225,thereby allowing the creation or otherwise updating of a securityapplication 211 according to evolving security needs.

The security services unit 220 includes different types of securityservices 221. Each security service 221 is designed to serve one or moresecurity applications apps) 211. The security services 221 are alsodesigned to provide efficient control and security data collection oversecurity rules and logs provided by the security products (150, FIG. 1).The classification of the security rules and logs into the services 221and one or more security engines (SEs) 225 of the services 221 isperformed by corresponding classifiers 250 as discussed in detail below.Each security service 221 may include one or more preconfigured securityengines 225.

Following are example security services 221 that can be maintained andexecuted by the security services unit 220. A first type of securityservice manages the products of network behavior analysis (NBA)products. Such service classifies the logs and/or rules of NBA productsinto a uniform set of protection functions (security engines) thattypifies NBA technologies such as abnormal data transfer, networkscanning, application scanning, brute force attack behavior malwarepropagation, etc.

Another type of security service 221 allows for managing and analyzingmultiple types of reputation sources (third party intelligence securitysources). The reputation database maintains reputation information ofnetwork entities such as clients and services (sites). Such reputationinformation may be used to evaluate if these entities can possess athreat. A threat may be, for example, a phishing site, a command andcontrol site, drop zone servers, sites that include malware software,and the like. The service classifies security capabilities of threatreputation feeds into a uniform set of protection functions (Securityengines) such as phishing, C&C, drop-point, malware sites, and so on.

Another type of security service 221 allows for control of multipletypes of anti-malware products in the network in order to analyzecontent such as web objects, mail attachments, executable files, and soon; and to identify anomalous code behavior. This service classifiessecurity logs of anti-malware (such as sand-box, network and endpointAVs) products into a uniform set of protection functions (Securityengines) that typifies these security technologies such as ransomware,droppers, memory scrapers, client spyware, etc.

Yet another type of security service 221 allows for management ofmultiple IDS and IPS devices. This service classifies securitycapabilities of IDS and IPS products into a uniform set of logicalprotection functions such as network scans, authentication brute-force,privileges escalation, malware, Command and control (C&C), a DoS,data-leak network patterns, and so on.

Some or all of the security services 221 may operate with a securityengine 225. A security engine 225 is configured with a set of enginerules, either manually or automatically. In some cases, a user canmodify and program new security engines 225 by defining a new set ofengine rules.

Yet another type of security service 221, which collect signals from allother services, generates real-time (RT) attack risk-chain patterns.These real-time attack risk-chain patterns represent cause-and-effectrelationships between the various security signals collected from thesecurity services. The risk chain pattern represents the overall “attackstory”, the stage and the intent of the attack such as ransomware attackcampaign, data-leak, and so on. These real-time attack risk-chainpatterns can be used for real-time triggering of investigation andmitigation actions against the threats.

It should be noted that programmability of the security stack 200 of thesystem 110 allows a user to select different types of security services221 and security engines 225, thereby providing a mix and matchcapability. Specifically, this capability is achieved by the securityservices 221, data plane unit 230, the classifiers 250, and a networkinterface module 113, all together which provides an abstraction layerfor all underlining data-plane security products in the network and forthreat intelligence DB (such as IDS, IPS, Anti-malware, NBA, reputationDB, WAF, and so on).

Information that is needed for operation of the security services 221may be retrieved from the data-plane unit 230, from the north boundinterface 240, or from both. It should be noted that the securityservices 221 in the security services unit 220 also communicate andinterface with the security applications unit 210.

It should be further noted that the security services 221 listed aboveare merely examples, and that other security services can be utilized inthe cyber-security system without departing from the scope of theembodiments disclosed herein. In various non-limiting embodiments, aprogramming language is provided in order to allow users to create andmodify security applications and to create and modify the securityengines included in each security service, as per business needs.

The data-plane unit 230 provides various functions that allow thesecurity services to both analyze network information and enforcedifferent control actions. Various services provided by the data planeunit 230 include topology discovery, data collection, QoS, and trafficcopy and redirection services which include traffic distribution (L2, L3load balancing for scaling out network products), identity managementservice and so on.

Topology discovery involves interacting with the data-plane networkelements, SDN controllers, and orchestration systems in order toretrieve network topology information.

The traffic copy and redirection services are designed to manage allnetwork traffic redirection functions which include, but are not limitedto, traffic redirection, smart traffic copying (copy based on L2-L4traffic filter parameters), traffic distribution, and so on.

The data collection may involve collecting statistics data from probesdeployed in the network and storing such statistics. The statisticscollection may include, but are not limited to, network-based statisticsfrom network elements; application-based network statistics from DPIproducts (including middle-boxes and servers); and user-based statisticsfrom network, DPI, middle boxes, and end-point products. The collectorservices normalize the statistical information into a format that can beanalyzed by the security services 221 in the security services unit 220.The QoS function involves interacting with a network and L4-L7 devicesin order to enforce, for example, traffic rate-limiting. An identitymanagement function involves interacting with identity managementsystems to provide name resolution services for the security services,map IP addresses to host, provide user names, and the opposite.

Also included in the security stack 200 are a plurality of classifiers250-1 through 250-q (hereinafter referred to individually as aclassifier 250 and collectively as classifiers 250, merely forsimplicity purposes) communicatively connected to the security servicesunit 220. Each classifier 250 is configured to classify security rulesand attack logs of different security products related to the samecategory of a cyber-solution to a respective security service 221 andits security engines 225. For example, a cyber-solution of an IDS with a“network scan” protection would be an option. Thus, all security rulesand/or logs related to a network scan type of threat of the differentsecurity products are classified to the same service and a network scansecurity engine of this service. It should be noted that one securityrule or attack log can be classified to one or more security services221 and engines 225 and thus become processed by one or more classifiers250.

In an embodiment, each classifier 250 is configured to normalize thesecurity rules, attack logs, or both, to a unified representation. Inanother embodiment, such normalization is performed by the networkinterface 113. The operation of a classifier 250 is discussed in greaterdetail in a U.S. patent application Ser. No. 15/227,571 assigned to thecommon assignee and it is hereby incorporated by reference for at thatit contains.

The north bound interface 240 interfaces between the system 110 and oneor more external systems (not shown). The external systems may include,for example, third party security analytics systems, security portals,datacenter orchestration control systems, identity management systems,or any other system that can provide information to the security stack.This enables wider context-based security decision making processes. Inan embodiment, the interfaces 240 may include standard interfaces, suchas CLI, REST APIs, Web user interfaces, as well as drivers that arealready programmed for control, configuration, or monitoring of specificthird-party systems, a combination thereof, and so on.

According to the disclosed embodiments, the DMO 270 is configured tocreate and customize security apps 211, such that the apps would bestfulfill the defense models. As noted above, a defense model is definedby a user (e.g., a security expert, an administrator, and the like). Asfurther noted above, the defense model is expressed by a base securityapplication, that when executed by the system 110, would provide thebest defense behavior. A security application 211 is a set of securityengines (SEs) 225 and at least one correlation rule, that is definedmanually, or automatically by a risk-chain service. The correlation ruledefines one or more logical operators to be applied on the securityengines 225.

According to an embodiment, a defense model is received (e.g., uploadedto, saved in, or generated in the system 110). Then, the availablesecurity engines 2250 and the scores of their respective securityproducts is determined. In one configuration, each security engine 225is associated with a security product(s) that can handle a specificthreat.

The operation of scoring security products is performed by each securityengine 225 operable in a service 221, designed (the service) to handle aspecific cyber-solution category. For example, a security service 221for an IDS can be configured with 3 different security engines, each ofwhich handles a different threat (e.g., privileges escalation, a networkscan, and a brute-force attack). Each engine 225 is configured to scorethe performance of each product (e.g., products provided by SourceFire®, McAfee®, Snort®, etc.) deployed in the network and configured tohandle the respective type of threat.

The scoring is performed based on a product profile (not shown in FIG.2). The product profile includes all classified security rules of aspecific product. The classified rules are in a unified format acrossthe different products. Thus, the scoring is agnostic to a specificrepresentation of product. The operation of a security engine 225 isfurther discussed herein below with reference to FIG. 5.

If a security engine 225 is not available, then there is no operableproduct (150, FIG. 1) that supports the needed functionality. Forexample, if a McAfee®'s network scan functionally is not configured, ornot functioning, the respective security engine 225, then would beidentified as not available. In an embodiment, all available securityengines 225 and their respective scores are maintained in a table (orother types of data structures) in the DMO 270.

The DMO 270 is configured to perform an analysis of the defense model.The analysis is performed, in part, to create a variant of the basesecurity application that would best match the defense model. A basesecurity application is a security application that matches therequirements defined in the security application.

In an embodiment, as an abstract example shown in FIG. 3, a defensemode, and hence its respective base application 310 may require theengines SE₁, SE₂, SE₃ (each of which describes a different capability).A capabilities table 330 indicates the available engine is only SE₃. Amapping table 335 lists SE′₁ and SE₄ as alternatives to SE₁ and SE₂,respectively, each of which is designated with its respective qualityscore. Thus, a newly created security application 320 would include theengines SE′₁ SE₄, and SE₃. The operation annotated in FIG. 3 as “L-OP”indicates any logical operator.

The newly created security application is added to the unit 210 andexecuted therein. In an embodiment, a notification is sent to a userabout the creation of the new application, its deployment, and/orexecution, the root-cause for creating the new application such as, butnot limited to, a product is missing, or a functionality within aproduct is missing, product failure, and so on. This allows the user toprevent or approve these actions.

For each application, the DMO 270 is configured to monitor the operationof the security engines 225 to determine any changes in theiroperational status. Any changes would trigger optimization of thesecurity application based on the current available security engines.

Referring back to the example in FIG. 3, if a SE₃ is not functioning,but SE₂ is available, then the security application 320 can be optimizedto include the engines SE′₁ and SE₂, resulting in a new application 330.

It should be noted that the DMO 270 is configured to perform theselections and replacement of security engines to comply with the logicstructure of the security applications, and specifically with thecorrelation rules defined between security engines (manually orautomatically by a risk-chain service). The correlation rules define arelationship among the security engines and their generated events. Thelogical operators may include, for example, OR, AND, XOR, NOT, IF-THEN,and the like.

In an embodiment, to create a fully functional and optimized securityapplication, first the DMO 270 identifies missing security engines,i.e., engines that are required in the base application, but are notavailable. Then, for each such missing engine an alternative replacementengine is selected.

In an example embodiment, the selection is made using a mapping table.The mapping table also includes a quality score, which is comparedaccording to the respective engine. As an example, the score may bebetween 0 and 1 determining how close (in terms of the applicationquality) the alternative engine is to the original (missing) engine. Thequality score can be a function of a number of factors, such asperformance scores of the original and alternative engine, theapplication type, an operating environment (e.g., an operating system),and the like.

Table 1 shows an example for a mapping table utilized by the DMO 270.

TABLE 1 Original Security Engine Alternative Security Engine Qualityscore IDS brute force NBA brute force 0.8 IDS malware activityReputation C&C 0.5 IDS Data Exfiltration NBA abnormal data transfer 0.6

As demonstrated in Table 1, the alternative for a missing “IDS bruteforce” security engine is the “NBA brute force” engine having a qualityscore of 0.8. Thus, replacing the IDS brute force engine with a “NBAbrute force” engine reduces the quality of the application. As furtherdemonstrated in Table 1, the “IDS malware activity” engine may bereplaced with the “Reputation C&C” engine. Also, the “IDS DataExfiltration” can be replaced with the “NBA abnormal data transfer”engine. It should be noted that security engines listed in Table 1 aremerely examples and multiple alternatives (each with different score)for each original security engine can be utilized.

In an embodiment, the mapping table may be (adaptively) adjusted basedon the performance results of the security applications utilizing thealternative security engines. That is, in case the “hits” (attack logsthat match the engine) are high for one or more applications with thesame alternative engine, then the DMO 270 may increase the quality scoreof that engine. In a similar fashion, in case of “misses” by one or moreapplications with the same alternative engine, then the DMO 270 maydecrease the quality score of that engine. In another embodiment, thescore of an engine is the signal to noise ratio (SNR) of the engine. TheSNR of engine is defined as the number of events generated in the pastand that successfully correlated with other events versus the number ofevents generated by the engine and were not correlated with otherevents.

In some embodiments, the mapping table is a matrix where a singleoriginal (missing) engine is mapped to two or more alternative engines.Such a matrix can represent the engines in the order that and thelogical operator to connect the two or more alternative engines. As anexample, a “IDS data exfiltration” security engine may be replaced withboth “NBA abnormal data transfer” and “NBA drop zone” security engines,correlated with an OR operator.

Upon selecting an alternative security engine, the DMO 270 performs areplacement process to replace such engine with the missing securityengine. The replacement is performed in a way that maintains therequired logical structure of the base application. In an embodiment,this includes placing the alternative security engine in the same placein the chain as the original security engine (that should be replaced).

For example, a security application (app₁) is defined through the usingthe following security engines and correction rule:

-   -   app₁→SE_(1 OR) SE_(2 OR) SE_(3 AND) SE₄        the variant of app₁ is app₂ where SE₂ and SE₃ are replaced with        the alternative engines SE′₂ and SE′₃.    -   app₂→SE_(1 OR) SE′_(2 OR) SE′_(3 AND) SE₄

In an embodiment, any missing security engines that cannot be replacedwith an alternative engine(s) should be removed from the applicationwhile maintaining the required logical structure. The removal process isdifferent for different logical operators. In an example embodiment, amissing engine connected through an OR operator to the other engine(s)is simply removed from the chain. For example, if SE₂ is missing thatthe variant of the base application (app₁) may be:

-   -   app₂→SE_(1 OR) SE_(3 AND) SE₄

It should be noted that that the removal of an engine connected with anOR operator is performed in order to increase the quality score of theentire application (app_score). An embodiment to compute the app_scoreis discussed below.

In another example, when two engines are connected through an ANDoperator, IF-THEN, AND with cross events, the mere removal of the enginecan break the logical structure of the security application. Inparticular, events or signals (processed the missing engines) should behandled. For example, when two security engines are connected with the‘AND’ operator and the second engine is chained with the first engine(e.g., the source host of the second engine is equal to the destinationhost of the first engine), then removing the first engine may preventassociated events from being detected by the second engine with theattack. To this end, the DMO 270 is configured to add logic rules tobridge the gap caused by removing a missing security engine. Forexample, one method to optimize the application in this case will be toremove the AND condition and alert the user about it.

Upon completing the creation of a new security application, an app_scoreis computed by the DMO 270 for each new application. In an embodiment,the app_score is the product of all quality scores of all engines in theapplication. For example, if an application implements only the 3alternative engines listed in Table 1, the app_score would be(0.8*0.5*0.6=0.24). The higher the quality score, the better the qualityof the security application. In an embodiment, only securityapplications having an app_score over a predefined threshold aredeployed, executed, and/or saved in the central repository 160 as shownin FIG. 1.

It should be noted that other methods can be used to compute theapp_score without departing from the disclosed embodiments. Such methodsmay include, for example, average, weight average, and the like.

It should be noted that each of the security applications unit 210, thesecurity services unit 220, the data plane unit 230, the north boundinterface 240, the classifiers 250, and the DMO 270, are communicativelyinterconnected through a predefined set of interfaces, APIs, or acombination of interfaces and APIs. It should be further noted that, inan embodiment, the security application unit 210, the security servicesunit 220, the data plane 230, the classifiers 250, and the DMO 270 230in the security stack 200 are independent. Thus, any changes in one unitor module do not necessarily result in any changes to the other modules.

Each, some, or all of the modules and the various units, modules andcomponents of the security stack 200 may be realized by a processingcircuity (not shown). The processing circuitry may comprise or be acomponent of a larger processing system implemented with one or moreprocessors. The one or more processors may be implemented with anycombination of general-purpose microprocessors, microcontrollers,digital signal processors (DSPs), field programmable gate array (FPGAs),programmable logic devices (PLDs), controllers, state machines, gatedlogic, discrete hardware components, dedicated hardware finite statemachines, or any other suitable entities that can perform calculationsor other manipulations of information.

The processing circuity (not shown) may also include machine-readablemedia (not shown) for storing software. Software shall be construedbroadly to mean any type of instructions, whether referred to assoftware, firmware, middleware, microcode, hardware descriptionlanguage, or otherwise. Instructions may include code (e.g., in sourcecode format, binary code format, executable code format, or any othersuitable format of code). The instructions, when executed by the one ormore processors, cause the processing system to perform the variousfunctions described herein.

FIG. 4 shows an example flowchart 400 illustrating a method for creatingand optimizing security applications to protect against cyber threatsaccording to an embodiment.

At S410, a defense model is obtained. In an embodiment, the defensemodel is obtained from a central repository. In another embodiment, thedefense model may be created or uploaded by a user. In yet anotherembodiment, the defense model can be obtained from a module or a systemconfigured to generate a defense model in response to a detected threat.As noted above, the defense model defines an optimal defense behavior ofa security platform with respect to a certain threat. To this end, thedefense model may designate one or more security capabilities (productsand/or engines) required to achieve the optimal defense.

At S420, the current available security capabilities are determined andevaluated. In an embodiment, S420 results with a list (or a table, e.g.,a capabilities table) of security engines that are currently available,giving a set of product that exist in the organization, and theirperformance scores. A performance score is computed based on a securityproduct classified to a respective security engine. In an embodiment,the performance score is based on any of, or combination of an offlinescore, a runtime score, a unified score, a SNR of the engine, or acombination thereof. An offline score is based on the security-rulesdefined in an attack database (not shown) of a respective securityproduct. A runtime score is generated based on attack logs provided by asecurity product. A unified score is at least based on the offline andruntime scores. An embodiment to compute the SNR (signal to noise) of anengine is discussed in detail above. The computation of a performancescore is further discussed with reference below and in theabove-referenced application Ser. No. 15/227,571.

At S430, based on the current available security capabilities, thedefense model is optimized. In an embodiment, S430 includes creating onemore security applications, each of which is a variant of a basesecurity application. The base security application defines the defensemodel.

As discussed in detail above, if the base security application definesthe optimal set of security engines, each variant may include a subsetof and/or alternative of such engines. In an example embodiment, thealternative security engines are selected based on a mapping table. Anexample for a mapping table is provided above.

As further noted above, the removal of the security engine is performedwhile maintaining the logical structure of the base securityapplication, and consequently maintaining the logical structure of thedefense model.

At S440, a quality application score (app_score) for each variantapplication is determined. In an embodiment, the quality score is aproduct of all performance scores of each security engines. Othertechniques for computing the app_score may be utilized without departingfrom the scope of the disclosed embodiments.

In an embodiment, S440 further includes selecting, based on theapp_score, a single security application from the variants of the createsecurity applications. For example, an application having the highestapp_score may be selected. In an embodiment, the selected applicationshould also demonstrate an app_score higher than a predefined threshold.In an embodiment, all created applications with an app_score higher thana predefined threshold are saved in the central repository.

At S450, the selected security application is deployed and executed.When executed, the selected security application can protect an entityin the enterprise against a specific cyber threat. This includesdetection, investigation, and/or mitigation. For example, an executedsecurity application may be configured to perform a ransomware attackcampaign detection and mitigation, intelligence gathering detection andmitigation, insider threat detection and mitigation, data-leaks, and soon. A deployment of a security application may include configuration ofthe relevant security products. Such configuration may include enablingor displaying security products or some functionalities therein. Itshould be noted that more than one application can be selected.

At S460, at least the security capabilities utilized in the deployedsecurity application are monitored to detect any changes in thefunctionality. For example, if a security product is currentlydysfunctional or its performance has been degraded. In yet anotherembodiment, it is checked if missing capabilities (engines) are nowavailable. At S470, it is checked if at least one changed has beendetected, and if so execution returns to S420 for reevaluation of thecapabilities; otherwise, execution continues with S480.

At S480, it is checked if execution should end, e.g., in response to auser request, end of a detected attack, and so on. If so, executionends; otherwise, execution returns to S460.

It should be noted that the method discussed with reference to FIG. 4 isperformed for each defense model. Thus, an optimization of a pluralityof models in parallel is possible.

FIG. 5 illustrates an example diagram of a security service 500demonstrating the computation of the performance scores according to anembodiment. In the example shown in FIG. 5, a plurality of securityproducts 510-1 through 510-R (hereinafter referred to individually as asecurity product 510 and collectively as security products 510, merelyfor simplicity purposes), some of which include an attack database ofthe attack databases 520-1 through 520-M, are analyzed by the securitysystem 550. The rules in the databases 520-1 through 520-M areclassified by a classifier 530 configured to generate product profiles(P₁, through P_(N)) stored in each of the security engines 540-1 through540-Q (hereinafter referred to individually as a security engine 540 andcollectively as security engines 540, merely for simplicity purposes) ofa security service 550. In additional, attack logs output, in runtime,by the security products 510-1 through 510-R are also classified by aclassifier 530 into the generated product profiles (P₁, through P_(N)).

Each security engine 540 is further configured to select a profile, andhence a security product, that demonstrates the best performance forhandling a specific cyber-threat. Each security engine 540 can applydifferent selection criteria as discussed in greater detail below. Asecurity engine 540 is configured to generate one or more of theoffline, runtime, and unified scores.

The offline score is based on the security-rules defined in an attackdatabase of a respective product. As such attack databases are typicallypopulated with rules, the score can be computed as an offline processand not based on the runtime operation of a security product 510. Itshould be noted that as the security rules in an attack database areupdated, added, or removed, a new offline score is generated.

The runtime score is generated or computed based on attack logs outputby a security product 510. The attack logs are generated at runtime,i.e., when the security product 510 is active in detecting and/orinvestigating, of an on-going attack. In some embodiments, a securityengine 540 can also generate a unified score based on the off-line andruntime scores.

It should be noted that, for some security services, only a run-timescore is generated. For example, run-time scores may only be generatedfor security products 510 having an attack database with security rulesthat frequently change or services that do not operate on securityrules. Each runtime or offline score can quantify the risk, or accuracy,or impact, threat coverage, or any combination thereof.

Each security engine 540 is configured to generate performance score(s)for handling a specific cyber-threat of a specific cyber-solutioncategory. For example, the security service 550 belongs to an IDScyber-solution category and the security engines 540 can individuallyhandle the following types of threats: privilege escalation, networkscan, and brute-force types of threats.

As another example, the security service 550 belongs to a reputationanalysis category and the security engines 540 can individually handlethe following types of threats: phishing web-sites, malware web-sites,and command and control web-sites. FIG. 6 shows an example block diagramof the system 110 according to another embodiment. The system 110includes a processing circuitry 610, a memory 615, a storage 620, and anetwork interface 630, all connected to a computer bus 640.

The processing circuitry 610 may be realized by one or more hardwarelogic components and circuits. Examples for such hardware logiccomponents and circuits are provided above. The memory 615 may bevolatile, non-volatile, or a combination thereof. The storage 620 may bemagnetic storage, optical storage, and the like.

In one configuration, computer readable instructions to implement one ormore embodiments disclosed herein may be stored in the storage 620. Thestorage 620 may also store other computer readable instructions toimplement an operating system, an application program, and the like.Computer readable instructions may be loaded in the memory for executionby the processing circuitry 610. The computer readable instructions,when executed, causes the processing circuitry 610 to perform theprocess for creating and optimizing security applications to protectagainst cyber threats and cyber-attacks as discussed in detail hereinabove.

In another embodiment, the storage 620, the memory 615, or both, areconfigured to store software. Software shall be construed broadly tomean any type of instructions, whether referred to as software,firmware, middleware, microcode, hardware description language, orotherwise. Instructions may include code (e.g., in source code format,binary code format, executable code format, or any other suitable formatof code). The instructions, when executed by the one or more processors,cause the processing circuitry 610 to perform the various functionsdescribed herein with respect to at least create and optimize securityapplications.

According to some embodiments, the storage 620 may be utilized to storeat least defense models, variant of created applications, capabilitiestable, and the mapping table.

The network interface 630 may include a wired connection or a wirelessconnection. The network interface 630 may be utilized to transmitcommunications media, to receive communications media, or both. In anembodiment, the network interface 630 provides an interface layer of thesystem 110. Such communication can be with SDN-based network elements or“legacy” network elements (not shown) in the network 120.

The network interface 630 supports bidirectional communication driversto allow communication with the data-plane elements includingconfigurations, policy reading, and logs collection. The drivers supportdifferent forms of communication standards and vendors' definedinterfaces such as, but not limited to, Netconf, Netflow, BGP, BGP flowspec, SSH, CLIs, DB APIs and more. The drivers enable communication withmiddle-box devices (e.g., L4-L7 devices and security devices, DPIdevices, etc.), end point devices (mobile, host-based securityapplications), server applications, management systems of these devices,combinations thereof, and so on. The network interface 1030 alsointerfaces with the plurality of security products designed to protectagainst different cyber threats. The computer bus 640 may be, forexample, a PCIe bus.

The various embodiments disclosed herein can be implemented as hardware,firmware, software, or any combination thereof. Moreover, the softwareis preferably implemented as an application program tangibly embodied ona program storage unit or computer readable medium consisting of parts,or of certain devices and/or a combination of devices. The applicationprogram may be uploaded to, and executed by, a machine comprising anysuitable architecture. Preferably, the machine is implemented on acomputer platform having hardware such as one or more central processingunits (“CPUs”), a memory, and input/output interfaces. The computerplatform may also include an operating system and microinstruction code.The various processes and functions described herein may be either partof the microinstruction code or part of the application program, or anycombination thereof, which may be executed by a CPU, whether or not sucha computer or processor is explicitly shown. In addition, various otherperipheral units may be connected to the computer platform such as anadditional data storage unit and a printing unit. Furthermore, anon-transitory computer readable medium is any computer readable mediumexcept for a transitory propagating signal.

It should be understood that any reference to an element herein using adesignation such as “first,” “second,” and so forth does not generallylimit the quantity or order of those elements. Rather, thesedesignations are generally used herein as a convenient method ofdistinguishing between two or more elements or instances of an element.Thus, a reference to first and second elements does not mean that onlytwo elements may be employed there or that the first element mustprecede the second element in some manner. Also, unless stated otherwisea set of elements comprises one or more elements. In addition,terminology of the form “at least one of A, B, or C” or “one or more ofA, B, or C” or “at least one of the group consisting of A, B, and C” or“at least one of A, B, and C” used in the description or the claimsmeans “A or B or C or any combination of these elements.” For example,this terminology may include A, or B, or C, or A and B, or A and C, or Aand B and C, or 2A, or 2B, or 2C, and so on.

All examples and conditional language recited herein are intended forpedagogical purposes to aid the reader in understanding the principlesof the disclosed embodiment and the concepts contributed by the inventorto furthering the art, and are to be construed as being withoutlimitation to such specifically recited examples and conditions.Moreover, all statements herein reciting principles, aspects, andembodiments of the disclosed embodiments, as well as specific examplesthereof, are intended to encompass both structural and functionalequivalents thereof. Additionally, it is intended that such equivalentsinclude both currently known equivalents as well as equivalentsdeveloped in the future, i.e., any elements developed that perform thesame function, regardless of structure.

What is claimed is:
 1. A method for optimizing a defense model usingavailable security capabilities, comprising: obtaining a defense model,wherein the defense model defines a defense behavior with respect to anidentified threat; obtaining a security application implementation ofthe defense model comprising a probability of success above apredetermined value, wherein an optimal security applicationimplementation defines an optimal set of security engines; evaluatingavailable security capabilities deployed in an enterprise environment todetermine a plurality of variant security applications implementing thedefense model by generating a list of currently available securityengines and their respective quality scores based on a performance scoreof each security engine defined in each of the variant securityapplications, wherein each variant security application includes atleast one of a subset of the optimal set of the security engines andalternative for security engines included the optimal set of thesecurity engines, wherein the performance score is based on at least oneof an offline score determined by an attack database of a respectivesecurity product, a runtime score determined by attack logs provided bythe respective security product, or a unified score determined by theoffline score and the runtime score; determining a quality score foreach variant security application of the plurality of variant securityapplications, the quality score reflecting a level of protection eachvariant security application offers against the identified threat;selecting, from the plurality of variant security applications, avariant security application having a highest quality score; andexecuting the selected variant security application to respond to theidentified threat.
 2. The method of claim 1, further comprising:deploying the selected variant security application in the enterpriseenvironment.
 3. The method of claim 1, wherein the defense model ispredefined and stored in a data repository.
 4. The method of claim 2,wherein each variant security application maintains a logical structureof the security application implementation of the defense model.
 5. Themethod of claim 1, wherein the selected variant security applicationprovides a unified abstract representation that is agnostic to securityproducts used for detection and mitigation of cyber threats.
 6. Themethod of claim 1, further comprising: monitoring the available securitycapabilities periodically during the execution of the selected variantsecurity application to identify any changes; and optimizing theselected variant security application during the execution when changesin the available security capabilities are detected.
 7. The method ofclaim 1, wherein the optimal set of security engines are operable in anorchestration system deployed in the enterprise environment, whereineach security engine is associate with a security capability executed bya security product deployed in the enterprise environment.
 8. The methodof claim 7, further comprising: optimizing the defense model upon afailure of the security product.
 9. A non-transitory computer readablemedium having stored thereon instructions for causing a processingcircuitry to execute a process for optimizing a defense model usingavailable security capabilities, the process comprising: obtaining adefense model, wherein the defense model defines a defense behavior withrespect to an identified threat; obtaining a security applicationimplementation of the defense model comprising a probability of successabove a predetermined value, wherein an optimal security applicationimplementation defines an optimal set of security engines; evaluatingavailable security capabilities deployed in an enterprise environment todetermine a plurality of variant security applications implementing thedefense model by generating a list of currently available securityengines and their respective quality scores based on a performance scoreof each security engine defined in each of the variant securityapplications, wherein each variant security application includes atleast one of a subset of the optimal set of the security engines andalternative for security engines included the optimal set of thesecurity engines, wherein the performance score is based on at least oneof an offline score determined by an attack database of a respectivesecurity product, a runtime score determined by attack logs provided bythe respective security product, or a unified score determined by theoffline score and the runtime score; determining a quality score foreach variant security application of the plurality of variant securityapplications, the quality score reflecting a level of protection eachvariant security application offers against the identified threat;selecting, from the plurality of variant security applications, avariant security application having a highest quality score; andexecuting the selected variant security application to respond to theidentified threat.
 10. A system for optimizing a defense model usingavailable security capabilities, comprising: a processing circuitry; anda memory coupled to the processing circuitry, the memory containstherein instructions that when executed by the processing circuitryconfigure the system to: obtain a defense model, wherein the defensemodel defines a defense behavior with respect to an identified threat;obtain a security application implementation of the defense modelcomprising a probability of success above a predetermined value, whereinan optimal security application implementation defines an optimal set ofsecurity engines; evaluate available security capabilities deployed inan enterprise environment to determine a plurality of variant securityapplications implementing the defense model by generating a list ofcurrently available security engines and their respective quality scoresbased on a performance score of each security engine defined in each ofthe variant security applications, wherein each variant securityapplication includes at least one of a subset of the optimal set of thesecurity engines and alternative for security engines included theoptimal set of the security engines, wherein the performance score isbased on at least one of an offline score determined by an attackdatabase of a respective security product, a runtime score determined byattack logs provided by the respective security product, or a unifiedscore determined by the offline score and the runtime score; determine aquality score for each variant security application of the plurality ofvariant security applications, the quality score reflecting a minimumlevel of protection each variant security application offers against theidentified threat; select, from the plurality of variant securityapplications, a variant security application having a highest qualityscore; and execute the selected variant security application to respondto the identified threat.
 11. The system of claim 10, wherein the systemis further configured to: deploy the selected variant securityapplication in the enterprise environment.
 12. The system of claim 10,wherein the defense model is predefined and stored in a data repository.13. The system of claim 11, wherein each variant security applicationmaintains a logical structure of the security application implementationof the defense model.
 14. The system of claim 10, wherein the selectedvariant security application provides a unified abstract representationthat is agnostic to security products used for detection and mitigationof cyber threats.
 15. The system of claim 10, wherein the system isfurther configured to: monitor the available security capabilitiesperiodically during the execution of the selected variant securityapplication to identify any changes; and optimize the selected variantsecurity application when changes in the available security capabilitiesare detected.
 16. The system of claim 10, wherein the security enginesare operable in an orchestration system deployed in the enterpriseenvironment, wherein each security engine is associate with a securitycapability executed by a security product deployed in the enterpriseenvironment.
 17. The system of claim 16, wherein the system is furtherconfigured to: optimize the defense model upon a failure of the securityproduct.